While it is best practice to decide which subjects to include into the second level analysis before computing and creating a GLM (which then contains the selected subjects), it sometimes happens that later analyses reveal the possibility that one (or several) of the included subjects are yet outliers.
In such a case it is convenient to (temporarily) remove such subjects from the GLM object and re-compute contrasts and correlations to observe the effect.
Note: this feature is not meant as encouragement to discard of subjects' data lightly! It is meant for cases where one is certain of the outlier status of those subjects, and recomputing a GLM requires a substantial amount of time!
A random-effects GLM file and the (list of) subject ID(s) that are to be discarded.
GLM::RemoveSubject - remove subject(s) from GLM FORMAT: [glm = ] glm.RemoveSubject(sid); Input fields: sid either single subject (char) or list of subjects (cell) Output fields: hfile altered GLM object
Assuming the GLM is loaded in variable
glm, the following syntax examples will work (given that the subject IDs specified exist!):